975 resultados para semantic processing


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Understanding of the shape and size of different features of the human body from scanned data is necessary for automated design and evaluation of product ergonomics. In this paper, a computational framework is presented for automatic detection and recognition of important facial feature regions, from scanned head and shoulder polyhedral models. A noise tolerant methodology is proposed using discrete curvature computations, band-pass filtering, and morphological operations for isolation of the primary feature regions of the face, namely, the eyes, nose, and mouth. Spatial disposition of the critical points of these isolated feature regions is analyzed for the recognition of these critical points as the standard landmarks associated with the primary facial features. A number of clinically identified landmarks lie on the facial midline. An efficient algorithm for detection and processing of the midline, using a point sampling technique, is also presented. The results obtained using data of more than 20 subjects are verified through visualization and physical measurements. A color based and triangle skewness based schemes for isolation of geometrically nonprominent features and ear region are also presented. [DOI: 10.1115/1.3330420]

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In this paper we focus on the challenging problem of place categorization and semantic mapping on a robot with-out environment-specific training. Motivated by their ongoing success in various visual recognition tasks, we build our system upon a state-of-the-art convolutional network. We overcome its closed-set limitations by complementing the network with a series of one-vs-all classifiers that can learn to recognize new semantic classes online. Prior domain knowledge is incorporated by embedding the classification system into a Bayesian filter framework that also ensures temporal coherence. We evaluate the classification accuracy of the system on a robot that maps a variety of places on our campus in real-time. We show how semantic information can boost robotic object detection performance and how the semantic map can be used to modulate the robot’s behaviour during navigation tasks. The system is made available to the community as a ROS module.

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A straightforward computation of the list of the words (the `tail words' of the list) that are distributionally most similar to a given word (the `head word' of the list) leads to the question: How semantically similar to the head word are the tail words; that is: how similar are their meanings to its meaning? And can we do better? The experiment was done on nearly 18,000 most frequent nouns in a Finnish newsgroup corpus. These nouns are considered to be distributionally similar to the extent that they occur in the same direct dependency relations with the same nouns, adjectives and verbs. The extent of the similarity of their computational representations is quantified with the information radius. The semantic classification of head-tail pairs is intuitive; some tail words seem to be semantically similar to the head word, some do not. Each such pair is also associated with a number of further distributional variables. Individually, their overlap for the semantic classes is large, but the trained classification-tree models have some success in using combinations to predict the semantic class. The training data consists of a random sample of 400 head-tail pairs with the tail word ranked among the 20 distributionally most similar to the head word, excluding names. The models are then tested on a random sample of another 100 such pairs. The best success rates range from 70% to 92% of the test pairs, where a success means that the model predicted my intuitive semantic class of the pair. This seems somewhat promising when distributional similarity is used to capture semantically similar words. This analysis also includes a general discussion of several different similarity formulas, arranged in three groups: those that apply to sets with graded membership, those that apply to the members of a vector space, and those that apply to probability mass functions.

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This study considers the scheduling problem observed in the burn-in operation of semiconductor final testing, where jobs are associated with release times, due dates, processing times, sizes, and non-agreeable release times and due dates. The burn-in oven is modeled as a batch-processing machine which can process a batch of several jobs as long as the total sizes of the jobs do not exceed the machine capacity and the processing time of a batch is equal to the longest time among all the jobs in the batch. Due to the importance of on-time delivery in semiconductor manufacturing, the objective measure of this problem is to minimize total weighted tardiness. We have formulated the scheduling problem into an integer linear programming model and empirically show its computational intractability. Due to the computational intractability, we propose a few simple greedy heuristic algorithms and meta-heuristic algorithm, simulated annealing (SA). A series of computational experiments are conducted to evaluate the performance of the proposed heuristic algorithms in comparison with exact solution on various small-size problem instances and in comparison with estimated optimal solution on various real-life large size problem instances. The computational results show that the SA algorithm, with initial solution obtained using our own proposed greedy heuristic algorithm, consistently finds a robust solution in a reasonable amount of computation time.

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Recent evidence from adult pronoun comprehension suggests that semantic factors such as verb transitivity affect referent salience and thereby anap- hora resolution. We tested whether the same semantic factors influence pronoun comprehension in young children. In a visual world study, 3-year- olds heard stories that began with a sentence containing either a high or a low transitivity verb. Looking behaviour to pictures depicting the subject and object of this sentence was recorded as children listened to a subsequent sentence containing a pronoun. Children showed a stronger preference to look to the subject as opposed to the object antecedent in the low transitivity condition. In addition there were general preferences (1) to look to the subject in both conditions and (2) to look more at both potential antecedents in the high transitivity condition. This suggests that children, like adults, are affected by semantic factors, specifically semantic prominence, when interpreting anaphoric pronouns.

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One of the problems encountered when photographic emulsions are used as the recording medium in holography is the appreciable time delay before the reconstruction can be viewed. This is largely due to the number of steps involved in processing and can be annoying in many applications.

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This paper addresses the problem of resolving ambiguities in frequently confused online Tamil character pairs by employing script specific algorithms as a post classification step. Robust structural cues and temporal information of the preprocessed character are extensively utilized in the design of these algorithms. The methods are quite robust in automatically extracting the discriminative sub-strokes of confused characters for further analysis. Experimental validation on the IWFHR Database indicates error rates of less than 3 % for the confused characters. Thus, these post processing steps have a good potential to improve the performance of online Tamil handwritten character recognition.

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Knowledge-based clusters are studied from the structural point of view. Generalized descriptions for such clusters are stated and illustrated. Peculiarities of certain knowledge-based cluster configurations are highlighted. The adequacy of the connectives logical and (“and”) logical or (“exclusive-or”) in describing such clusters is justified. The definition of “concept” is elaborated from the clustering point of view and used to establish the equivalence between, descriptions of clusters and concepts. The order-independence of semantic-directed clustering approach is established formally based on axiomatic considerations.

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One of the biggest challenges when considering polymer nanocomposites for electrical insulation applications lies in determining their electrical properties accurately, which in turn depend on several factors, primary being dispersion of particles in the polymer matrix. With this background, this paper reports an experimental study to understand the effects of different processing techniques on the dispersion of filler particles in the polymer matrix and their related effect on the dielectric properties of the composites. Polymer composite and nanocomposite samples for the study were prepared by mixing 10% by weight of commercially available TiO2 particles of two different sizes in epoxy using different processing methods. A considerable effect of the composite processing method could be seen in the dielectric properties of nanocomposites.

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Processing maps developed on the basis of the Dynamic Materials Model provide valuable information that might help the metal working industry in solving problems related to workability and microstructural control in commercial alloys. In this research, the processing maps for an as-cast AZ31 magnesium alloy are presented. The results are validated via microstructural observations, clearly delineating safe and unsafe regimes for further process design of this alloy.

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High-Tc superconducting thin films can be deposited and processed by pulsed and CW lasers, and a respectable materials technology for the Y-Ba-Cu-O superconductor is rapidly emerging. The pulsed laser deposition technique is simple because it produces films with compositions nearly identical to those of the target pellets. A larger variety of substrates can be used, compared to other deposition technologies, because of the relatively low temperature requirements. The laser deposition mechanism has been investigated. As-deposited superconducting films, epitaxial films with smooth surfaces, and multilayer structures with abrupt interfaces have been produced. The electrical transport properties can be changed locally using a focused argon-ion laser by modifying the oxygen stoichiometry. This laser writing can be erased by room-temperature exposure to an oxygen plasma. Other laser patterning methods such as material removal, melt-quench, and direct pattern transfer are being developed.

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Ex-situ grown thin films of SrBi2Nb2O9 (SBN) were deposited on platinum substrates using laser ablation technique. A low substrate-temperature-processing route was chosen to avoid any diffusion of bismuth into the Pt electrode. It was observed that the as grown films showed an oriented growth along the 'c'-axis (with zero spontaneous polarization). The as grown films were subsequently annealed to enhance crystallization. Upon annealing, these films transformed into a polycrystalline structure, and exhibited excellent ferroelectric properties. The switching was made to be possible by lowering the thickness without losing the electrically insulating behavior of the films. The hysteresis results showed an excellent square-shaped loop with results (P-r = 4 muC/cm(2) E-c = 90 kV/cm) in good agreement with the earlier reports. The films also exhibited a dielectric constant of 190 and a dissipation factor of 0.02, which showed dispersion at low frequencies. The frequency dispersion was found to obey Jonscher's universal power law relation, and was attributed to the ionic charge hopping process according to earlier reports. The de transport studies indicated an ohmic behavior in the low voltage region, while higher voltages induced a bulk space charge and resulted in non-linear current-voltage dependence.

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The alloy, Ti-6Al-4V is an alpha + beta Ti alloy that has large prior beta grain size (similar to 2 mm) in the as cast state. Minor addition of B (about 0.1 wt.%) to it refines the grain size significantly as well as produces in-situ TiB needles. The role played by these microstructural modifications on high temperature deformation processing maps of B-modified Ti64 alloys is examined in this paper.Power dissipation efficiency and instability maps have been generated within the temperature range of 750-1000 degrees C and strain rate range of 10(-3)-10(+1) s(-1). Various deformation mechanisms, which operate in different temperature-strain rate regimes, were identified with the aid of the maps and complementary microstructural analysis of the deformed specimens. Results indicate four distinct deformation domains within the range of experimental conditions examined, with the combination of 900-1000 degrees C and 10(-3)-10(-2) s(-1) being the optimum for hot working. In that zone, dynamic globularization of alpha laths is the principle deformation mechanism. The marked reduction in the prior beta grain size, achieved with the addition of B, does not appear to alter this domain markedly. The other domains, with negative values of instability parameter, show undesirable microstructural features such as extensive kinking/bending of alpha laths and breaking of beta laths for Ti64-0.0B as well as generation of voids and cracks in the matrix and TiB needles in the B-modified alloys. (C) 2010 Elsevier B.V. All rights reserved.

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The Intelligent Decision Support System (IDSS), also called an expert system, is explained. It was then applied to choose the right composition and firing temperature of a ZnO based varistor. 17 refs.